get_subscription_events

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely non-obvious semantics: 'counts are events, not users' and 'connected=false means no webhook is connected', both of which affect interpretation of the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and enumerated contents are front-loaded, followed by two short clarifying sentences. It is dense but every clause earns its place; no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of explaining return content and does so well by listing event categories and cohorts. Minor gap: it does not state the response shape (keying by day/country) beyond the high-level grouping.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with both 'days' (window 1-365, default 90) and 'appId' (from list_apps) fully documented in the schema. The description adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (subscription event counts for one app) and enumerates exactly what is counted (trial starts, conversions, renewals, cancellations, refunds, billing issues, revenue, cohorts). The source is pinned to the RevenueCat/Adapty webhook, making it distinguishable from revenue/analytics siblings without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the data description (subscription webhook events from RevenueCat/Adapty), but there is no explicit when-to-use or when-not guidance, and it never routes the agent away from overlapping siblings like get_revenue. The 'connected=false' note hints at a precondition but is not framed as actionable guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.